Sentiment Analysis with Python NLTK Text Classification

This is a demonstration of sentiment analysis using a
NLTK 2.0.4 powered text classification process.
It can tell you whether it thinks the text you enter below expresses
positive sentiment,
negative sentiment, or if it's
neutral. Using hierarchical classification,
neutrality is determined first, and sentiment polarity is
determined second, but only if the text is not neutral.

Analyze Sentiment

Language

Enter text

Enter up to 50000 characters

How Sentiment Analysis with Text Classification Works

The english sentiment uses classifiers trained on both twitter sentiment
as well as movie reviews from the data sets created by
Bo Pang and Lillian Lee
using nltk-trainer
(also on bitbucket).
The dutch sentiment is based on book reviews.

The results will be more accurate on text that is similar to original training data.
If you get an odd result, it could be the words you've used are unrecognized.
Try entering more words to improve accuracy.

Sentiment Analysis Articles

To read more about how it works, please read the following articles I've written about the process: